code: def __init__(self, nb_classes, sz_embed, mrg=0.1, alpha=32):
      torch.nn.Module.__init__(self)
      # Proxy Anchor Initialization
      self.proxies = torch.nn.Parameter(
          torch.randn(nb_classes, sz_embed)
      )
      nn.init.kaiming_normal_(self.proxies, mode="fan_out")
  
      self.nb_classes = nb_classes
      self.sz_embed = sz_embed
      self.mrg = mrg
      self.alpha = alpha
  
file_path: pytorch-metric-learning/tests/losses/test_proxy_anchor_loss.py
imports: from contextlib import nullcontext
  import torch
  import torch.nn
  import torch.nn.functional
  import unittest
  import torch
  from pytorch_metric_learning.losses import ProxyAnchorLoss
  from ..None import TEST_DEVICE, TEST_DTYPES
  from ..zzz_testing_utils.testing_utils import angle_to_coord
label_desc: Use image node_id 1 to create a new OriginalImplementationProxyAnchor object from inherited base classes: torch.nn with example: obj = OriginalImplementationProxyAnchor(nb_classes, sz_embed, mrg, alpha)